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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM14699

Traffic Analysis and Vehicle Flow Control using Deep Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM14699

Volume:

6 |

6 |

Jun 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM14699

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DK

Dr.S.Thulasi Krishna

N

Nagarjuna

PD

P.Rama Devi

PM

P.Venu Madhav

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Abstract

In recent times, traffic congestion is a main problem at every junction.Traffic timer controlling system will display green signal for each lane at regular time intervals.If a lane does not consists of vehicles,the traffic controlling system still display the green signal for a period of time.At that time, vehicles at other lanes has to wait for the signal.This problem is prevented by the project “ TRAFFIC ANALYSIS AND FLOW CONTROL USING YOLO-v3. “YOLO-v3 stands for “You Look Only Once” and it is a real-time object detection algorithm that identifies objects in videos, images and helpful for detect object in environment. This project is developed for regulating the traffic flow by releasing better signal at time intervals

KEYWORDS

Traffic flow YOLO-v3 Deep Learning

Cite This Article

Dr.S.Thulasi Krishna, Nagarjuna, P.Rama Devi, P.Venu Madhav, "Traffic Analysis and Vehicle Flow Control using Deep Learning," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 6, Jun 2022. https://doi.org/10.55041/IJSREM14699

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Publication Date

6/16/2022

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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